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If we want to evaluate a pitch, there are few things we can focus on. We can look at the qualities of the pitch itself as it moves toward home plate, including movement, pitch type, and location. We can look at the catcher's glove, to see how much it moves from its target. We can look at the batter, to see how balanced he is as he swings at it. And we can look at the result: hit, out, stung, dribbled. I have a theory, which is that we (non-scouts) are mostly unable to make much of the first, second and third ways. That, mostly, we only remember the fourth.

So what follows is an experiment. I don't know what the point of this experiment is or what it will show. I don't know the best way to conduct this experiment. This might be an experiment I revisit in a better form someday in the future. But the experiment is simple, and I think it will be interesting, and I can't wait.

Last week, Jake Peavy started a game against the Twins. It was a kind of a classic BABIP-buster game. He struck out seven and walked one; he didn't allow a home run. But he gave up 10 hits and three runs, and he took the loss. Twins batters put 20 balls in play, and 10 became hits. This raises the question of whether BABIP failed Peavy, or whether Peavy failed BABIP, and whether these hits were his fault. MOD CUT

For those of you that think that hits given up are mostly the result of bad pitching, it should be possible to correctly identify which pitches led to hits, right?

1. The hit is on the right (73 percent of you were correct)
2. Right (30 percent)
3. Right (30 percent)
4. Right (37 percent)
5. Left (61 percent)
6. Left (22 percent)
7. Left (63 percent)
8. Right (76 percent)
9. Right (79 percent)

It is helpful to see the results broken down like this. If I just tell you that you got 52 percent correct, you might conclude that your guesses were basically random. You might think that there was nothing significant that distinguished one pitch from another, to your educated-but-amateur eyes. But in fact, as a group, you were not random, and you did not guess with 52 percent accuracy on each set. We actually spotted certain features that we thought were significant, and in some sets those features perhaps were significant. In others, we were wildly misled.